期刊
OPTICS AND LASERS IN ENGINEERING
卷 100, 期 -, 页码 267-278出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.optlaseng.2017.09.013
关键词
Digital image correlation; Interpolation bias; Inverse compositional Gauss Newton algorithm; Fourier analysis; Gradient estimator
类别
资金
- National Natural Science Foundation of China [11332010, 11702287, 11627803, 11472266, 11372300]
- Chinese Academy of Sciences [XDB22040502]
It is believed that the classic forward additive Newton-Raphson (FA-NR) algorithm and the recently introduced inverse compositional Gauss-Newton (IC-GN) algorithm give rise to roughly equal interpolation bias. Questioning the correctness of this statement, this paper presents a thorough analysis of interpolation bias for the IC-GN algorithm. A theoretical model is built to analytically characterize the dependence of interpolation bias upon speckle image, target image interpolation, and reference image gradient estimation. The interpolation biases of the FA-NR algorithm and the IC-GN algorithm can be significantly different, whose relative difference can exceed 80%. For the IC-GN algorithm, the gradient estimator can strongly affect the interpolation bias; the relative difference can reach 178%. Since the mean bias errors are insensitive to image noise, the theoretical model proposed remains valid in the presence of noise. To provide more implementation details, source codes are uploaded as a supplement. (C) 2017 Elsevier Ltd. All rights reserved.
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